Addressing Data Imbalance in Hydrological Machine Learning: Impact of Advanced Sampling Methods on Performance and Interpretability

Guardat en:

Dades bibliogràfiques
Publicat a:	Water Resources Research vol. 61, no. 10 (Oct 1, 2025)
Autor principal:	Yin, Xiaoran
Altres autors:	Shu, Longcang, Wang, Zhe, Zhou, Long, Niu, Shuyao, Ren, Huazhun, Liu, Bo, Lu, Chengpeng
Publicat:	John Wiley & Sons, Inc.
Matèries:	Hydrologic data Datasets Algorithms Sampling methods Soil properties Hydraulic conductivity Hydrology Machine learning Hypercubes Random sampling Performance evaluation Learning algorithms Contamination Accuracy Soil sciences Training Groundwater Statistical sampling Decision making National forests Hydraulics Latin hypercube sampling Environmental
Accés en línia:	Citation/Abstract Full Text Full Text - PDF
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!

Sigues el primer a deixar un comentari!